Mohamed A. Mahdi1, Suliman Mohamed Fati2,*, Mohamed A.G. Hazber1, Shahanawaj Ahamad3, Sawsan A. Saad4
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1651-1671, 2024, DOI:10.32604/cmes.2024.052291
Abstract Cyberbullying, a critical concern for digital safety, necessitates effective linguistic analysis tools that can navigate the complexities of language use in online spaces. To tackle this challenge, our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers (BERT) base model (cased), originally pretrained in English. This model is uniquely adapted to recognize the intricate nuances of Arabic online communication, a key aspect often overlooked in conventional cyberbullying detection methods. Our model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media (SM) tweets showing a notable… More >
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